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NEW QUESTION 43
You have a dataset that contains information about taxi journeys that occurred during a given period.
You need to train a model to predict the fare of a taxi journey.
What should you use as a feature?

  • A. the trip ID of individual taxi journeys
  • B. the trip distance of individual taxi journeys
  • C. the number of taxi journeys in the dataset
  • D. the fare of individual taxi journeys

Answer: B

Explanation:
Section: Describe fundamental principles of machine learning on Azure
Explanation/Reference:
Explanation:
The label is the column you want to predict. The identified Featuresare the inputs you give the model to predict the Label.
Example:
The provided data set contains the following columns:
vendor_id: The ID of the taxi vendor is a feature.
rate_code: The rate type of the taxi trip is a feature.
passenger_count: The number of passengers on the trip is a feature.
trip_time_in_secs: The amount of time the trip took. You want to predict the fare of the trip before the trip is completed. At that moment, you don’t know how long the trip would take. Thus, the trip time is not a feature and you’ll exclude this column from the model.
trip_distance: The distance of the trip is a feature.
payment_type: The payment method (cash or credit card) is a feature.
fare_amount: The total taxi fare paid is the label.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/predict-prices

 

NEW QUESTION 44
You have a database that contains a list of employees and their photos.
You are tagging new photos of the employees.
For each of the following statements select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/overview
https://docs.microsoft.com/en-us/azure/cognitive-services/face/concepts/face-detection

 

NEW QUESTION 45
Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. dataset
  • B. module
  • C. compute
  • D. pipeline

Answer: A,B

Explanation:
Explanation
You can drag-and-drop datasets and modules onto the canvas.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

 

NEW QUESTION 46
Which two scenarios are examples of a conversational AI workload? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. a telephone answering service that has a pre-recorder message
  • B. telephone voice menus to reduce the load on human resources
  • C. a chatbot that provides users with the ability to find answers on a website by themselves
  • D. a service that creates frequently asked questions (FAQ) documents by crawling public websites

Answer: B,C

Explanation:
Explanation
B: A bot is an automated software program designed to perform a particular task. Think of it as a robot without a body.
C: Automated customer interaction is essential to a business of any size. In fact, 61% of consumers prefer to communicate via speech, and most of them prefer self-service. Because customer satisfaction is a priority for all businesses, self-service is a critical facet of any customer-facing communications strategy.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/ai-overview
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/interactive-voice-response-bot

 

NEW QUESTION 47
……

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